Nasser et l’exode des Sépharades d’Égypte

Cet article se propose d’analyser, dans une perspective proche de la micro-histoire de Carlo Ginzburg, un corpus de quatre romans de langues différentes (italien, espagnol, anglais et français) tous centrés sur l’exil forcé de quatre familles séfarades de l’Egypte de Nasser. En raison de son ancrage dans l’histoire factuelle, de son polyglottisme et de la thématique d’inspiration vétérotestamentaire (l’exode) qui sert de toile de fond aux quatre histoires racontées, le corpus constitue un microcosme littéraire d’une sensibilité et d’une grâce peu communes.Quest’articolo si propone, nell'ottica della microstoria di ispirazione ginzburghiana, di trattare un corpus di quattro opere romanzesche di lingua diversa (italiano, spagnolo, inglese, francese), tutte e quattro incentrate sull'esilio forzato di quattro famiglie sefardite dall'Egitto di Nasser. In virtù dello stretto legame con la storia fattuale, del poliglottismo e della tematica d’ispirazione veterotestamentaria (l'esodo) che fa da sfondo alle quattro vicende raccontate, il corpus rappresenta un microcosmo letterario di una sensibilità e di una grazia fuori dal comune

Treebar Maps: Schematic Representation of Networks at Scale

Many data sets, crucial for today's applications, consist essentially of enormous networks, containing millions or even billions of elements. Having the possibility of visualizing such networks is of paramount importance. We propose an algorithmic framework and a visual metaphor, dubbed treebar map, to provide schematic representations of huge networks. Our goal is to convey the main features of the network's inner structure in a straightforward, two-dimensional, one-page drawing. This drawing effectively captures the essential quantitative information about the network's main components. Our experiments show that we are able to create such representations in a few hundreds of seconds. We demonstrate the metaphor's efficacy through visual examination of extensive graphs, highlighting how their diverse structures are instantly comprehensible via their representations.Comment: 27 pages, 32 figures, 1 tabl

Growth and Physical Structure of Amorphous Boron Carbide Deposited by Magnetron Sputtering on a Silicon Substrate with a Titanium Interlayer

Multilayer amorphous boron carbide coatings were produced by radiofrequency magnetron sputtering on silicon substrates. To improve the adhesion, titanium interlayers with different thickness were interposed between the substrate and the coating. Above three hundreds nanometer, the enhanced roughness of the titanium led to the growth of an amorphous boron carbide with a dense and continuing columnar structure, and no delamination effect was observed. Correspondingly, the adhesion of the coating became three time stronger than in the case of a bare silicon substrate. Physical structure and microstructural proprieties of the coatings were investigated by means of a scan electron microscopy, atomic force microscopy and X-ray diffraction. The adhesion of the films was measured by a scratch tester

Design, Validation and CFD Modeling of an Environmental Wind Tunnel

The wind erosion of granular materials stored within the open yards of industrial plants (i.e., industrial wind erosion) and the subsequent emission and dispersion of particulate matter (PM) in the surrounding areas represent an important issue for the exposed population and for the environment as a whole. The Environment Impact Assessment (EIA) and the design of emission control measures require a deep knowledge of the erosion phenomenon, and the precise estimation of the Emission Factors (EF) associated with the specific PM source under investigation. Aiming to characterize the emission potential of industrial granular materials, a new Environmental Wind Tunnel (EWT) has recently been built at the Department of Civil and Environmental Engineering and Architecture (DICAAR) laboratories, in Cagliari University. The article discusses the EWT’s updated design and the set-up methodologies applied to reproduce the Atmospheric Boundary Layer (ABL) acting over the surfaces of coarse and heterogeneous granular materials. In addition, a Computational Fluid Dynamics (CFD) model of the EWT has been developed to reproduce and analyze the wind field throughout the entire tunnel volume and preliminarily evaluate possible modifications to the original design. The accuracy of the simulation has been verified by comparing the CFD model and the results of the experimental tests

Growth and Physical Structure of Amorphous Boron Carbide Deposited by Magnetron Sputtering on a Silicon Substrate with a Titanium Interlayer

Multilayer amorphous boron carbide coatings were produced by radiofrequency magnetron sputtering on silicon substrates. To improve the adhesion, titanium interlayers with different thickness were interposed between the substrate and the coating. Above three hundreds nanometer, the enhanced roughness of the titanium led to the growth of an amorphous boron carbide with a dense and continuing columnar structure, and no delamination effect was observed. Correspondingly, the adhesion of the coating became three time stronger than in the case of a bare silicon substrate. Physical structure and microstructural proprieties of the coatings were investigated by means of a scan electron microscopy, atomic force microscopy and X-ray diffraction. The adhesion of the films was measured by a scratch tester

Learning new physics efficiently with nonparametric methods

We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. Based on the original proposal by D'Agnolo and Wulzer (arXiv:1806.02350), the model evaluates the compatibility between experimental data and a reference model, by implementing a hypothesis testing procedure based on the likelihood ratio. Model-independence is enforced by avoiding any prior assumption about the presence or shape of new physics components in the measurements. We show that our approach has dramatic advantages compared to neural network implementations in terms of training times and computational resources, while maintaining comparable performances. In particular, we conduct our tests on higher dimensional datasets, a step forward with respect to previous studies.Comment: 22 pages, 13 figure

The rapid FEV(1) decline in chronic obstructive pulmonary disease is associated with predominant emphysema: a longitudinal study.

Early identification of patients with COPD and prone to more rapid decline in lung function is of particular interest from both a prognostic and therapeutic point of view. The aim of this study was to identify the clinical, functional and imaging characteristics associated with the rapid FEV(1) decline in COPD.Between 2001 and 2005, 131 outpatients with moderate COPD in stable condition under maximum inhaled therapy underwent clinical interview, pulmonary function tests and HRCT imaging of the chest and were followed for at least 3 years.Twenty-six percent of patients had emphysema detected visually using HRCT. The FEV(1) decline was 42 ± 66 mL/y in the total sample, 88 ± 76 mL/y among rapid decliners and 6 ± 54 mL/y among the other patients. In the univariable analysis, the decline of FEV(1) was positively associated with pack-years (p0.05), emphysema at HRCT (p0.001), RV (p0.05), FRC (p0.05), FEV(1) (p0.01) at baseline and with number of hospitalizations per year (p0.05) during the follow-up. Using multivariable analysis, the presence of emphysema proved to be an independent prognostic factor of rapid decline (p = 0.001). When emphysema was replaced by RV, the model still remained significant.The rapid decline in lung function may be identified by the presence of emphysema at HRCT or increased RV in patients with a long smoking history